OpenRaiser/Intern-Atlas huggingface dataset:
An Occlusion Reasoning Scheme for Monocular Pedestrian Tracking in Dynamic Scenes
Venue: arXiv cs.CV 2015
Year: 2015

This paper looks into the problem of pedestrian tracking using a monocular, potentially moving, uncalibrated camera. The pedestrians are located in each frame using a standard human detector, which are then tracked in subsequent frames. This is a challenging problem as one has to deal with complex situations like changing background, partial or full occlusion and camera motion. In order to carry out successful tracking, it is necessary to resolve associations between the detected windows in the current frame with those obtained from the previous frame. Compared to methods that use temporal windows incorporating past as well as future information, we attempt to make decision on a frame-by-frame basis. An occlusion reasoning scheme is proposed to resolve the association problem between a pair of consecutive frames by using an affinity matrix that defines the closeness between a pair of windows and then, uses a binary integer programming to obtain unique association between them. A second stage of verification based on SURF matching is used to deal with those cases where the above optimization scheme might yield wrong associations. The efficacy of the approach is demonstrated through experiments on several standard pedestrian datasets.
TSP with Time Windows and Service Time
Venue: arXiv cs.DS 2015
Year: 2015

We consider TSP with time windows and service time. In this problem we receive a sequence of requests for a service at nodes in a metric space and a time window for each request. The goal of the online algorithm is to maximize the number of requests served during their time window. The time to traverse an edge is the distance between the incident nodes of that edge. Serving a request requires unit time. We characterize the competitive ratio for each metric space separately. The competitive ratio depends on the relation between the minimum laxity (the minimum length of a time window) and the diameter of the metric space. Specifically, there is a constant competitive algorithm depending whether the laxity is larger or smaller than the diameter. In addition, we characterize the rate of convergence of the competitive ratio to $1$ as the laxity increases. Specifically, we provide a matching lower and upper bounds depending on the ratio between the laxity and the TSP of the metric space (the minimum distance to traverse all nodes). An application of our result improves the lower bound for colored packets with transition cost and matches the upper bound. In proving our lower bounds we use an interesting non-standard embedding with some special properties. This embedding may be interesting by its own.
Dynamics of Belief: Abduction, Horn Knowledge Base And Database Updates
Venue: arXiv cs.LO 2015
Year: 2015

The dynamics of belief and knowledge is one of the major components of any autonomous system that should be able to incorporate new pieces of information. In order to apply the rationality result of belief dynamics theory to various practical problems, it should be generalized in two respects: first it should allow a certain part of belief to be declared as immutable; and second, the belief state need not be deductively closed. Such a generalization of belief dynamics, referred to as base dynamics, is presented in this paper, along with the concept of a generalized revision algorithm for knowledge bases (Horn or Horn logic with stratified negation). We show that knowledge base dynamics has an interesting connection with kernel change via hitting set and abduction. In this paper, we show how techniques from disjunctive logic programming can be used for efficient (deductive) database updates. The key idea is to transform the given database together with the update request into a disjunctive (datalog) logic program and apply disjunctive techniques (such as minimal model reasoning) to solve the original update problem. The approach extends and integrates standard techniques for efficient query answering and integrity checking. The generation of a hitting set is carried out through a hyper tableaux calculus and magic set that is focused on the goal of minimality. The present paper provides a comparative study of view update algorithms in rational approach. For, understand the basic concepts with abduction, we provide an abductive framework for knowledge base dynamics. Finally, we demonstrate how belief base dynamics can provide an axiomatic characterization for insertion a view atom to the database. We give a quick overview of the main operators for belief change, in particular, belief update versus database update.
S-AMP for Non-linear Observation Models
Venue: arXiv cs.IT 2015
Year: 2015

Recently we extended Approximate message passing (AMP) algorithm to be able to handle general invariant matrix ensembles. In this contribution we extend our S-AMP approach to non-linear observation models. We obtain generalized AMP (GAMP) algorithm as the special case when the measurement matrix has zero-mean iid Gaussian entries. Our derivation is based upon 1) deriving expectation propagation (EP) like algorithms from the stationary-points equations of the Gibbs free energy under first- and second-moment constraints and 2) applying additive free convolution in free probability theory to get low-complexity updates for the second moment quantities.
Online Optimization : Competing with Dynamic Comparators
Venue: arXiv cs.LG 2015
Year: 2015

Recent literature on online learning has focused on developing adaptive algorithms that take advantage of a regularity of the sequence of observations, yet retain worst-case performance guarantees. A complementary direction is to develop prediction methods that perform well against complex benchmarks. In this paper, we address these two directions together. We present a fully adaptive method that competes with dynamic benchmarks in which regret guarantee scales with regularity of the sequence of cost functions and comparators. Notably, the regret bound adapts to the smaller complexity measure in the problem environment. Finally, we apply our results to drifting zero-sum, two-player games where both players achieve no regret guarantees against best sequences of actions in hindsight.
On a Family of Decomposable Kernels on Sequences
Venue: arXiv cs.LG 2015
Year: 2015

In many applications data is naturally presented in terms of orderings of some basic elements or symbols. Reasoning about such data requires a notion of similarity capable of handling sequences of different lengths. In this paper we describe a family of Mercer kernel functions for such sequentially structured data. The family is characterized by a decomposable structure in terms of symbol-level and structure-level similarities, representing a specific combination of kernels which allows for efficient computation. We provide an experimental evaluation on sequential classification tasks comparing kernels from our family of kernels to a state of the art sequence kernel called the Global Alignment kernel which has been shown to outperform Dynamic Time Warping
On the Secrecy Exponent of the Wire-tap Channel
Venue: arXiv cs.IT 2015
Year: 2015

We derive an exponentially decaying upper-bound on the unnormalized amount of information leaked to the wire-tapper in Wyner's wire-tap channel setting. We characterize the exponent of the bound as a function of the randomness used by the encoder. This exponent matches that of the recent work of Hayashi (2011) which is, to the best of our knowledge, the best exponent that exists in the literature. Our proof---like those of Han et al. (2014) and Hayashi (2015)---is exclusively based on an i.i.d. random coding construction while that of Hayashi (2011), in addition, requires the use of random universal hash functions.
Random Access in DVB-RCS2: Design and Dynamic Control for Congestion Avoidance
Venue: arXiv cs.IT 2015
Year: 2015

In the current DVB generation, satellite terminals are expected to be interactive and capable of transmission in the return channel with satisfying quality. Considering the bursty nature of their traffic and the long propagation delay, the use of a random access technique is a viable solution for such a Medium Access Control (MAC) scenario. In this paper, random access communication design in DVB-RCS2 is considered with particular regard to the recently introduced Contention Resolution Diversity Slotted Aloha (CRDSA) technique. This paper presents a model for design and tackles some issues on performance evaluation of the system by giving intuitive and effective tools. Moreover, dynamic control procedures that are able to avoid congestion at the gateway are introduced. Results show the advantages brought by CRDSA to DVB-RCS2 with regard to the previous state of the art.
Solitaire Chess is NP-complete
Venue: arXiv cs.CC 2015
Year: 2015

"Solitaire Chess" is a logic puzzle published by Thinkfun, that can be seen as a single person version of traditional chess. Given a chess board with some chess pieces of the same color placed on it, the task is to capture all pieces but one using only moves that are allowed in chess. Moreover, in each move one piece has to be captured. We prove that deciding if a given instance of Solitaire Chess is solvable is NP-complete.
The Anatomy of Relevance: Topical, Snippet and Perceived Relevance in Search Result Evaluation
Venue: arXiv cs.IR 2015
Year: 2015

Currently, the quality of a search engine is often determined using so-called topical relevance, i.e., the match between the user intent (expressed as a query) and the content of the document. In this work we want to draw attention to two aspects of retrieval system performance affected by the presentation of results: result attractiveness ("perceived relevance") and immediate usefulness of the snippets ("snippet relevance"). Perceived relevance may influence discoverability of good topical documents and seemingly better rankings may in fact be less useful to the user if good-looking snippets lead to irrelevant documents or vice-versa. And result items on a search engine result page (SERP) with high snippet relevance may add towards the total utility gained by the user even without the need to click those items. We start by motivating the need to collect different aspects of relevance (topical, perceived and snippet relevances) and how these aspects can improve evaluation measures. We then discuss possible ways to collect these relevance aspects using crowdsourcing and the challenges arising from that.
Construction of Quasi-Cyclic Product Codes
Venue: arXiv cs.IT 2015
Year: 2015

Linear quasi-cyclic product codes over finite fields are investigated. Given the generating set in the form of a reduced Gr{ö}bner basis of a quasi-cyclic component code and the generator polynomial of a second cyclic component code, an explicit expression of the basis of the generating set of the quasi-cyclic product code is given. Furthermore, the reduced Gr{ö}bner basis of a one-level quasi-cyclic product code is derived.
Back to the Past: Source Identification in Diffusion Networks from Partially Observed Cascades
Venue: arXiv cs.SI 2015
Year: 2015

When a piece of malicious information becomes rampant in an information diffusion network, can we identify the source node that originally introduced the piece into the network and infer the time when it initiated this? Being able to do so is critical for curtailing the spread of malicious information, and reducing the potential losses incurred. This is a very challenging problem since typically only incomplete traces are observed and we need to unroll the incomplete traces into the past in order to pinpoint the source. In this paper, we tackle this problem by developing a two-stage framework, which first learns a continuous-time diffusion network model based on historical diffusion traces and then identifies the source of an incomplete diffusion trace by maximizing the likelihood of the trace under the learned model. Experiments on both large synthetic and real-world data show that our framework can effectively go back to the past, and pinpoint the source node and its initiation time significantly more accurately than previous state-of-the-arts.
A Simple Observer for Gyro and Accelerometer Biases in Land Navigation Systems
Venue: arXiv cs.SY 2015
Year: 2015

In various applications of land vehicle navigation and automatic guidance systems, Global Navigation Satellite System/Inertial Measurement Unit (GNSS/IMU) positioning performance crucially depends on the attitude determination accuracy affected by gyro and accelerometer bias instabilities. Traditional bias estimation approaches based on the Kalman filter suffer from implementation complexity and require non-intuitive tuning procedures. In this paper we propose, as an alternative, a simple observer that estimates inertial sensor biases exclusively in terms of quantities with obvious geometrical meaning. By this, any multidimensional vector-matrix operations are avoided and observer tuning is substantially simplified. The observer has been successfully tested in a farming vehicle navigation system.
Manipulating the Probabilistic Serial Rule
Venue: arXiv cs.GT 2015
Year: 2015

The probabilistic serial (PS) rule is one of the most prominent randomized rules for the assignment problem. It is well-known for its superior fairness and welfare properties. However, PS is not immune to manipulative behaviour by the agents. We initiate the study of the computational complexity of an agent manipulating the PS rule. We show that computing an expected utility better response is NP- hard. On the other hand, we present a polynomial-time algorithm to compute a lexicographic best response. For the case of two agents, we show that even an expected utility best response can be computed in polynomial time. Our result for the case of two agents relies on an interesting connection with sequential allocation of discrete objects.
A High-Rate MSR Code With Polynomial Sub-Packetization Level
Venue: arXiv cs.IT 2015
Year: 2015

We present a high-rate $(n,k,d=n-1)$-MSR code with a sub-packetization level that is polynomial in the dimension $k$ of the code. While polynomial sub-packetization level was achieved earlier for vector MDS codes that repair systematic nodes optimally, no such MSR code construction is known. In the low-rate regime (i. e., rates less than one-half), MSR code constructions with a linear sub-packetization level are available. But in the high-rate regime (i. e., rates greater than one-half), the known MSR code constructions required a sub-packetization level that is exponential in $k$. In the present paper, we construct an MSR code for $d=n-1$ with a fixed rate $R=\frac{t-1}{t}, \ t \geq 2,$ achieveing a sub-packetization level $α= O(k^t)$. The code allows help-by-transfer repair, i. e., no computations are needed at the helper nodes during repair of a failed node.
Spatially-Coupled MacKay-Neal Codes Universally Achieve the Symmetric Information Rate of Arbitrary Generalized Erasure Channels with Memory
Venue: arXiv cs.IT 2015
Year: 2015

This paper investigates the belief propagation decoding of spatially-coupled MacKay-Neal (SC-MN) codes over erasure channels with memory. We show that SC-MN codes with bounded degree universally achieve the symmetric information rate (SIR) of arbitrary erasure channels with memory. We mean by universality the following sense: the sender does not need to know the whole channel statistics but needs to know only the SIR, while the receiver estimates the transmitted codewords from channel statistics and received words. The proof is based on potential function.
Enhancing the performance of Decoupled Software Pipeline through Backward Slicing
Venue: arXiv cs.PL 2015
Year: 2015

The rapidly increasing number of cores available in multicore processors does not necessarily lead directly to a commensurate increase in performance: programs written in conventional languages, such as C, need careful restructuring, preferably automatically, before the benefits can be observed in improved run-times. Even then, much depends upon the intrinsic capacity of the original program for concurrent execution. The subject of this paper is the performance gains from the combined effect of the complementary techniques of the Decoupled Software Pipeline (DSWP) and (backward) slicing. DSWP extracts threadlevel parallelism from the body of a loop by breaking it into stages which are then executed pipeline style: in effect cutting across the control chain. Slicing, on the other hand, cuts the program along the control chain, teasing out finer threads that depend on different variables (or locations). parts that depend on different variables. The main contribution of this paper is to demonstrate that the application of DSWP, followed by slicing offers notable improvements over DSWP alone, especially when there is a loop-carried dependence that prevents the application of the simpler DOALL optimization. Experimental results show an improvement of a factor of ?1.6 for DSWP + slicing over DSWP alone and a factor of ?2.4 for DSWP + slicing over the original sequential code.
A Cheap System for Vehicle Speed Detection
Venue: arXiv cs.CV 2015
Year: 2015

The reliable detection of speed of moving vehicles is considered key to traffic law enforcement in most countries, and is seen by many as an important tool to reduce the number of traffic accidents and fatalities. Many automatic systems and different methods are employed in different countries, but as a rule they tend to be expensive and/or labor intensive, often employing outdated technology due to the long development time. Here we describe a speed detection system that relies on simple everyday equipment - a laptop and a consumer web camera. Our method is based on tracking the license plates of cars, which gives the relative movement of the cars in the image. This image displacement is translated to actual motion by using the method of projection to a reference plane, where the reference plane is the road itself. However, since license plates do not touch the road, we must compensate for the entailed distortion in speed measurement. We show how to compute the compensation factor using knowledge of the license plate standard dimensions. Consequently our system computes the true speed of moving vehicles fast and accurately. We show promising results on videos obtained in a number of scenes and with different car models.
Mixed Map Labeling
Venue: arXiv cs.CG 2015
Year: 2015

Point feature map labeling is a geometric problem, in which a set of input points must be labeled with a set of disjoint rectangles (the bounding boxes of the label texts). Typically, labeling models either use internal labels, which must touch their feature point, or external (boundary) labels, which are placed on one of the four sides of the input points' bounding box and which are connected to their feature points by crossing-free leader lines. In this paper we study polynomial-time algorithms for maximizing the number of internal labels in a mixed labeling model that combines internal and external labels. The model requires that all leaders are parallel to a given orientation $θ\in [0,2π)$, whose value influences the geometric properties and hence the running times of our algorithms.
A Canonical Form for Weighted Automata and Applications to Approximate Minimization
Venue: arXiv cs.FL 2015
Year: 2015

We study the problem of constructing approximations to a weighted automaton. Weighted finite automata (WFA) are closely related to the theory of rational series. A rational series is a function from strings to real numbers that can be computed by a finite WFA. Among others, this includes probability distributions generated by hidden Markov models and probabilistic automata. The relationship between rational series and WFA is analogous to the relationship between regular languages and ordinary automata. Associated with such rational series are infinite matrices called Hankel matrices which play a fundamental role in the theory of minimal WFA. Our contributions are: (1) an effective procedure for computing the singular value decomposition (SVD) of such infinite Hankel matrices based on their representation in terms of finite WFA; (2) a new canonical form for finite WFA based on this SVD decomposition; and, (3) an algorithm to construct approximate minimizations of a given WFA. The goal of our approximate minimization algorithm is to start from a minimal WFA and produce a smaller WFA that is close to the given one in a certain sense. The desired size of the approximating automaton is given as input. We give bounds describing how well the approximation emulates the behavior of the original WFA.
Self-Calibration and Biconvex Compressive Sensing
Venue: arXiv cs.IT 2015
Year: 2015

The design of high-precision sensing devises becomes ever more difficult and expensive. At the same time, the need for precise calibration of these devices (ranging from tiny sensors to space telescopes) manifests itself as a major roadblock in many scientific and technological endeavors. To achieve optimal performance of advanced high-performance sensors one must carefully calibrate them, which is often difficult or even impossible to do in practice. In this work we bring together three seemingly unrelated concepts, namely Self-Calibration, Compressive Sensing, and Biconvex Optimization. The idea behind self-calibration is to equip a hardware device with a smart algorithm that can compensate automatically for the lack of calibration. We show how several self-calibration problems can be treated efficiently within the framework of biconvex compressive sensing via a new method called SparseLift. More specifically, we consider a linear system of equations y = DAx, where both x and the diagonal matrix D (which models the calibration error) are unknown. By "lifting" this biconvex inverse problem we arrive at a convex optimization problem. By exploiting sparsity in the signal model, we derive explicit theoretical guarantees under which both x and D can be recovered exactly, robustly, and numerically efficiently via linear programming. Applications in array calibration and wireless communications are discussed and numerical simulations are presented, confirming and complementing our theoretical analysis.
On the genetic optimization of APSK constellations for satellite broadcasting
Venue: arXiv cs.IT 2015
Year: 2015

Both satellite transmissions and DVB applications over satellite present peculiar characteristics that could be taken into consideration in order to further exploit the optimality of the transmission. In this paper, starting from the state-of-the-art, the optimization of the APSK constellation through asymmetric symbols arrangement is investigated for its use in satellite communications. In particular, the optimization problem is tackled by means of Genetic Algorithms that have already been demonstrated to work nicely with complex non-linear optimization problems like the one presented hereinafter. This work aims at studying the various parameters involved in the optimization routine in order to establish those that best fit this case, thus further enhancing the constellation.